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Baig Academy

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Baig Academy

Free Resources — Baig Academy
100% Free · No Credit Card

Everything You Need
to Get Started — Free.

Hands-on challenges, full walkthrough recordings, and a growing community. Built for beginners. No fluff. Start your journey right here.

155k+
Real salary records
2,000+
Learners inside
4
Free challenges
2
Full recordings
15 min per challenge
Your pace — no deadlines
Stuck? Check the recording
Dataset inside each challenge
Hands-On Practice

Work through them at your own pace.

Each challenge builds on the last. Start with the basics and end up building your own complete data benchmarks in Python.

📊
Challenge 1 · Featured
1 Week Python Challenge
6 hands-on challenges using 155,000+ real salary records. Load data, filter, group, visualise, and build your own salary benchmark — step by step.
6 challenges Real dataset Beginner
Start Challenge
🔌
Challenge 2 · Intermediate
API Integration
Move beyond static datasets. Learn how to pull live data from real APIs, handle JSON responses, and integrate external data into Python.
APIs & JSON Live data Python
Start Challenge
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Challenge 3
ML Models Bootcamp
Build and evaluate real machine learning models. Understand how algorithms perform on data and what drives predictions.
scikit-learn Predictions
⏳ Coming Soon
Video Walkthroughs

Watch how the instructor teaches.

Full walkthrough recordings so you never get stuck. See the exact thought process, code execution, and explanations behind each challenge.

🎬
Full Walkthrough
1 Week Challenge Solution
Complete walkthrough of all 6 challenges. Watch Rahim work through the real dataset from scratch — every line of code explained.
Python & Pandas Live coding
🧠
Webinar Replay
ML Models Introduction
The full recording of our live webinar. An introduction to machine learning models with real examples, live Q&A, and hands-on demos.
Machine Learning Concepts
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  • ✓ Early access to upcoming ML Challenge
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  • Cohort Starting Soon

Python for Data & AI

Stop copying AI code. Build real analytical logic in our upcoming live cohort.

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